Survey of semi-supervised semantic segmentation
Survey of semi-supervised semantic segmentation
A Survey on Semi-Supervised Semantic Segmentation
arXiv paper abstract https://arxiv.org/abs/2302.09899
arXiv PDF paper https://arxiv.org/pdf/2302.09899.pdf
Semantic segmentation is one of the most challenging tasks in computer vision.
However, in many applications, a frequent obstacle is the lack of labeled images, due to the high cost of pixel-level labeling.
In this scenario, it makes sense to approach the problem from a semi-supervised point of view, where both labeled and unlabeled images are exploited.
In recent years this line of research has gained much interest and many approaches have been published in this direction.
... objective ... is to provide an overview of the current state of the art in semi-supervised semantic segmentation, offering an updated taxonomy of all existing methods to date.
This is complemented by an experimentation with a variety of models representing all the categories of the taxonomy on the most widely used benchmark datasets in the literature ...
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